Development of innovative multi-epitope mRNA vaccine against Pseudomonas aeruginosa using in silico approaches

Abstract The rising issue of antibiotic resistance has made treating Pseudomonas aeruginosa infections increasingly challenging. Therefore, vaccines have emerged as a viable alternative to antibiotics for preventing P. aeruginosa infections in susceptible individuals. With its superior accuracy, high efficiency in stimulating cellular and humoral immune responses, and low cost, mRNA vaccine technology is quickly replacing traditional methods. This study aimed to design a novel mRNA vaccine by using in silico approaches against P. aeruginosa. The research team identified five surface and antigenic proteins and selected their appropriate epitopes with immunoinformatic tools. These epitopes were then examined for toxicity, allergenicity and homology. The researchers also checked their presentation and identification by major histocompatibility complex cells and other immune cells through valuable tools like molecular docking. They subsequently modeled a multi-epitope protein and optimized it. The mRNA was analyzed in terms of structure and stability, after which the immune system’s response against the new vaccine was simulated. The results indicated that the designed mRNA construct could be an effective and promising vaccine that requires laboratory and clinical trials.


INTRODUCTION
Pseudomonas aeruginosa is a Gram-negative bacillus that causes severe infections in patients with burns, severe wounds and pneumonia, as well as in critically ill patients who require intubation (ventilator-associated pneumonia) or catheterization (urinary tract infections) [1,2].The emergence of antibiotic-resistant strains has made treating P. aeruginosa infections increasingly difficult [3].According to the World Health Organization, there is an urgent need for novel therapeutics to combat P. aeruginosa infections due to their increasing prevalence and resistance rates.Pseudomonas aeruginosa is listed as one of the three bacterial species for which there is the most critical need for developing novel therapeutics [4].
In the USA, multi-drug-resistant (MDR) P. aeruginosa caused 32 600 infections among hospitalized patients and an estimated 2700 deaths in 2017 [5].Resistance rates of P. aeruginosa are increasing in many parts of the world, with recent studies reporting the widespread presence of extensively drug-resistant (XDR) high-risk clones in healthcare settings [6,7].Therefore, researchers are exploring several evolving strategies for the control and therapy of P. aeruginosa, including immunotherapy, phage therapy and vaccination [8].Vaccines are a promising alternative to antibiotics in preventing P. aeruginosa infections in susceptible individuals [9].They may be the best strategy to overcome treatment-associated complications with MDR P. aeruginosa.Several vaccines have entered clinical trials to prevent P. aeruginosa infections, but none have been approved for human use [10].
Over the years, vaccine development research has made significant progress.Traditional approaches like living attenuated, inactivated bacteria and subunit vaccines have proven to induce immunogenicity and provide long-term protection [11].However, novel methods such as peptide-based and DNA vaccines show potential for rapid and scalable vaccine development [12][13][14].Unfortunately, peptide-based vaccines have a low immunogenicity index, and DNA vaccines carry the risk of insertional mutagenesis into the host's DNA.On the other hand, mRNA vaccines are more efficient, addressing the safety and efficacy concerns that arise with DNA and peptide-based vaccines [15,16].In addition, cell-free mRNA vaccines can be produced quickly, costeffectively and at scale.Furthermore, a single mRNA vaccine can encode multiple antigens, enhancing the immune response against resilient pathogens [17].
In designing an effective mRNA vaccine for P. aeruginosa, surface proteins critical for binding and entering the bacteria into host cells could serve as suitable targets.The outer membrane of P. aeruginosa contains various proteins, including lipoproteins and channels.Porins, which are β-barrel proteins that create water-filled diffusion channels, control nutrient exchange across the outer membrane.Among porin proteins, OprF is a significant target for diagnosing and treating P. aeruginosa because it is highly expressed, antigenically conserved and immunogenic [4,18].Another essential surface lipoprotein in P. aeruginosa pathogenesis is Outer membrane protein I (OprI), which plays a significant role in making the bacteria resistant to antimicrobial peptides.A phase III clinical trial vaccine (NCT01563263) consisting of OprI and OprF proteins shows promise as a vaccine for P. aeruginosa [19].
T4 pilli in P. aeruginosa are critical in many processes, including attachment to biotic and abiotic surfaces, DNA uptake, biofilm formation, phage transduction, and twitching motility.Therefore, they provide an ideal target antigen for vaccine development [20].The pilus fiber comprises hundreds of copies of PilA or pilin, which act as both a major structural subunit and an adhesion factor [21].Pseudomonas aeruginosa is equipped with a single polar f lagellum, comprising a filament made of helically arranged polymerized f lagellin subunits (FliC), a type-specific cap protein (FliD), the hook at the base of the filament (FlgE), two filament-hook junction proteins (FlgKL) and several basal body components across outer and inner membranes [22].FliC f lagellin (paFliC) is crucial for P. aeruginosa colonization and acts as an essential virulence factor.It activates innate immune responses by recognizing Tolllike receptor 5 (TLR5) and adaptive immunity in the host.paFliC has been considered a vaccine candidate against P. aeruginosa infections [23].In this study, a novel multi-epitope mRNA vaccine was designed against P. aeruginosa using in silico approaches.

Prediction of immune cell epitopes
To predict B-cell epitopes, the ABCpred webserver available at https://webs.iiitd.edu.in/raghava/abcpred/ABC was used.An artificial machine-learning approach was employed for epitope prediction, with each protein sequence submitted using a 0.5 threshold.The selected epitope length was 16 amino acids, and the overlap filter remained active.The top epitope results were further investigated [24].
In addition, cytotoxic T-cell lymphocyte (CTL) epitopes were predicted using the ANN 4.0 method through the Immune Epitope Database MHC, which can be accessed at http://tools.iedb.org/main/tcell/.Predicted epitopes were sorted based on their IC 50 value.Helper T-cell lymphocytes were predicted using the NNalign method through the Immune Epitope Database MHC-II, which can be accessed at http://tools.iedb.org/main/tcell/[25].

Human homology
To check for homology between the predicted peptides and human peptides, the NCBI BLASTp tool available at https://blast.ncbi.nlm.nih.gov/Blast.cgiPAGE=Proteins was used to compare all peptides against the Homo sapiens (TaxID: 9606) protein database.Peptides with an E-value greater than 0.05 were considered possibly non-homologous to human peptides.

Prediction of epitope's antigenicity, allergenicity and toxicity
To evaluate the antigenicity, allergenicity and toxicity of selected epitopes, various web servers were used.The VaxiJen web server available at http://www.ddg-pharmfac.net/Vaxijen/VaxiJen/VaxiJen.html predicted antigenicity based on the physicochemical properties of the epitopes in an alignment-independent manner, with a focus on bacteria and a threshold of 0.4.The AllerTop V.2.0 webserver at http://www.ddg-pharmfac.net/AllerTOP was used to predict allergenicity of epitopes using default settings.Lastly, the ToxinPred server available at https://webs.iiitd.edu.in/raghava/toxinpred/multi_submit.phppredicted and measured toxicity of epitopes by generating all potential mutants using default settings.Only epitopes that were antigenic, non-toxic and non-allergenic were retained for further research.

Molecular docking between T-lymphocyte epitopes and MHC alleles
Molecular docking simulations were used to evaluate the binding affinity of selected T-lymphocyte epitopes to their corresponding major histocompatibility complex (MHC) alleles.The 3D structures of MHC alleles were obtained from the RCSB PDB database and processed using PyMOL software to remove unnecessary ligands.Energy minimization of the structures was performed using Swiss-PDB Viewer.The selected epitopes were folded into their respective three-dimensional structures using the PEP-FOLD 3.5 server and then energy minimized using Swiss-PdBViewer before docking.Docking was performed using the ClusPro 2.0 server available at https://cluspro.bu.edu/login.php.

Design of the vaccine construct
A proposed mRNA vaccine construct has been designed using a specific sequence order from the N to C terminus.The sequence includes a modified cap structure (m7GCap), followed by a 5 untranslated region (5 UTR) and a Kozak sequence to enhance translation.The coding region begins with a signal peptide (tPA) connected through an EAAAK linker to an adjuvant component (RpfE), separated by a GPGPG linker.The vaccine's epitopes have been grouped into three sets and linked together via AAY, KK and GPGPG linkers, which provide cleavability, f lexibility, rigidity, and separate domains for proper folding and functioning of the components.The HTL epitopes are connected to the LBL epitopes using the KK linker, while the LBL epitopes are connected to the CTL epitopes via an AAY linker.The mRNA construct terminates with a MITD sequence, followed by a stop codon, a 3 UTR and a poly(A) tail to ensure proper termination and stability of the mRNA molecule.This sequence offers a promising approach to developing vaccines against certain diseases.

Prediction of antigenicity, allergenicity, toxicity and physicochemical properties of the vaccine construct
To determine the antigenicity of the mRNA vaccine construct, the VaxiJen 2.0 and ANTIGENpro servers were utilized.VaxiJen 2.0 predicts based on the physicochemical properties of the vaccine, while ANTIGENpro uses machine-learning algorithms and microarray analysis data.The constructed mRNA vaccine's amino acid sequence were used as the input, excluding tPA and MITD sequences.To assess allergenicity, the AllerTOP 2.0 server was used, and the ToxinPred server predicted toxicity.Finally, the ProtParam online web server (https://web.expasy.org/protparam/) was employed to predict various physicochemical properties of the vaccine, including amino acid composition, molecular weight, theoretical isoelectric point (pI), instability index (II), aliphatic index (A.I.) and grand average of hydropathicity (GRAVY).

In silico immune simulation
The C-ImmSim online simulation server (http://150.146.2.1/ CIMMSIM/index.php) was utilized to simulate the immune response for the mRNA vaccine construct.An immune response is stimulated by this server using epitopes in conjunction with lymphocyte receptors.To simulate the recommended dosage schedule of current vaccines, three doses of 1000 vaccine units were administered over 4 weeks.For the purposes of this study, all parameters were set to default values, and the injections were administered at time-steps 1, 84 and 168.By conducting a dynamic simulation of the immune response, the performance of the mRNA vaccine construct and its potential efficacy in eliciting an immune response can be assessed by researchers.

Codon optimization of the vaccine construct
The codon sequences in the designed mRNA vaccine construct were optimized to ensure efficient expression within human cells.For this purpose, the GenSmart Codon Optimization Tool (http:// www.genscript.com/)provided by GenScript (G.S.) was used.After optimization, a quality assessment of the optimized sequence was performed using the Rare Codon Analysis tools (http://www.genscript.com/)also provided by GenScript.The efficiency of mRNA translation was determined using Codon Adaptation Index (CAI).In addition, any unusual tandem codons present in the optimized sequence were identified through codon frequency distribution analysis.By optimizing the codon sequences, the expression and efficacy of the mRNA vaccine construct can potentially be improved by researchers.

Secondary structure prediction of the designed mRNA vaccine
The RNAfold tool (http://rna.tbi.univie.ac.at/cgi-bin/RNAWebSuite/RNAfold.cgi), which is part of the Vienna RNA Package 2.0, was used to determine the predicted secondary structure of the mRNA vaccine construct.McCaskill's algorithm was utilized by the RNAfold tool to calculate the minimum free energy (MFE) of the predicted secondary structure.Through this tool, researchers obtained information on both the minimal free energy structure and the centroid secondary structure, as well as their respective minimum free energies.By predicting the secondary structure of the mRNA vaccine construct, researchers can gain a better understanding of its potential stability and functionality within human cells.

Prediction and validation of the secondary and tertiary structures of the designed vaccine
The PSIPRED server (http://bioinf.cs.ucl.ac.uk/psipred/) was used by researchers to predict the secondary structure of the peptide sequence in the mRNA vaccine construct, excluding the tPA signal and MITD sequences.This tool employs position-specific scoring matrices and has an accuracy rate of 84.2%.To predict the three-dimensional structure of the peptide sequence, the Robetta server (https://robetta.bakerlab.org/)was utilized, which generated five possible structures.The ProSA-web (https:// prosa.services.came.sbg.ac.at/prosa.php),PROCHECK and ERRAT (https://saves.mbi.ucla.edu/)servers were then used to verify the best structure.By predicting both the secondary and tertiary structures of the peptide sequence, researchers can gain a better understanding of its potential function within the mRNA vaccine construct.

Prediction of the conformational B-cell epitopes
ElliPro, an online server (http://tools.iedb.org/ellipro/),was employed to identify discontinuous B-cell epitopes within the studied protein structure.ElliPro uses the geometrical characteristics of the 3D model to predict these epitopes.Compared to other available prediction tools for discontinuous B-cell epitopes, ElliPro provides the highest AUC value of 0.732 for any protein model.By identifying these epitopes, researchers can gain a better understanding of the potential immunogenicity of the protein structure and its role in the overall efficacy of the mRNA vaccine construct.The identification of these epitopes can also aid in the development of future vaccines and immunotherapies.

Molecular docking of the designed vaccine
The ClusPro server was utilized to determine the potential interaction between the desired mRNA vaccine and toll-like receptor 4 (TLR-4) or toll-like receptor 3 (TLR-3).The 3D structures of both the vaccine and TLR-4 (PDB ID: 3FXI) or TLR-3 (PDB ID: 1ZIW) were docked using the PIPER docking algorithm.By predicting how the vaccine structure interacts with TLR-4 or TLR-3, researchers can gain a better understanding of the potential immunogenicity of the vaccine construct and its overall efficacy in eliciting an immune response.

Molecular dynamics simulation
To confirm the physical motions of atoms and molecules within the TLR4-vaccine and TLR3-vaccine complex structures, dynamics simulation analysis was conducted using the iMODS server (http://imods.chaconlab.org/).The complex structures with the lowest binding energy were utilized for this analysis to ensure accuracy.The movement of atoms and molecules within the complex structures over time was simulated and their stability was assessed through the iMODS server.By understanding the dynamic behavior of the complex structures, insight into their potential efficacy in eliciting an immune response can be gained by the researchers.

Prediction and estimation of B-cell epitopes
In this study, the selection of epitopes was limited to the top five predicted for each included protein by the ABCpred webserver.The selected epitopes were subjected to further filtering to ensure their antigenicity, non-allergenicity and non-toxicity, using the VaxiJen, AllerTop and ToxinPred web servers, respectively.To avoid the induction of autoimmunity by the vaccine construct, all predicted epitopes were screened for homologs among Homo sapiens (Taxid:9606) with an E-value <0.05 and any homologs found were excluded from the vaccine construct.The selected protein variants were downloaded from the NCBI database and aligned using the Bioedit 7.2 program.In total, five B-cell epitopes extracted from the five studied proteins were chosen for inclusion in the vaccine construct, as listed in Table 1.

Prediction and estimation of the CTL epitopes
In this study, the researchers used the IEDB database to identify potential cytotoxic T lymphocyte (CTL) epitopes from the nine proteins studied.Epitopes with an IC 50 over 500 were selected for further analysis.Only epitopes that were antigenic, nonallergenic, non-toxic and non-homologs were included in the subsequent analysis.From these selection criteria, 11 epitopes located in the conserved regions of the proteins were chosen for inclusion in the vaccine construct.By selecting conserved epitopes, the researchers aimed to create a vaccine with broad efficacy against multiple strains of the target virus or pathogen.The selected epitopes are listed in Table 1.

Prediction and estimation of the HTL epitopes
Several potential HTL epitopes were identified from studying five P. aeruginosa proteins mentioned previously.Epitopes that were antigenic, non-allergenic, non-toxic, and non-homologs were investigated for their ability to induce cytokines, specifically IL-4, IL-10 and IFN-γ .From these analyses, 18 epitopes located in the conserved regions of the proteins were chosen for inclusion in the vaccine construct.These epitopes induced the cytokines mentioned earlier and are listed in Table 1.By selecting epitopes that induce cytokine responses, the researchers aimed to enhance the immune response elicited by the vaccine construct.

Molecular docking between MHC alleles and the selected T-lymphocyte epitopes
In this study, the researchers identified 29 lymphocyte epitopes that recognized a total of 38 MHC alleles, with some epitopes binding to one allele and others binding to multiple alleles (Table 2).Four epitopes and their corresponding MHC alleles were selected for further molecular docking analysis, with the crystallographic structures of all MHC alleles selected from the RCSB PDB server (Table 2).Using ClusPro 2.0, molecular docking was performed on these four epitopes and their parallel MHC alleles, and the results are presented in Table 3.The epitope LSDGAAAGY displayed the strongest binding affinity with its corresponding MHC allele (HLA-A * 01:01) with a −643.6 kcal/mol value.Furthermore, it was found that this epitope fits perfectly inside the binding cleft of its corresponding allele (Figure 1B).Finally, the interactions between the epitope and various residues of the MHC allele were evaluated using the LIGPLOT website (Figure 2).

Evaluation of antigenicity, allergenicity, toxicity and physicochemical properties of the vaccine construct
To assess the antigenicity, allergenicity and toxicity of the vaccine construct, the VaxiJen, ANTIGENpro, AllerTop and Toxin-Pred servers were utilized by the researchers.In addition, the physicochemical properties of the vaccine were evaluated using the ProtParam server (Table 4).The results indicated that the vaccine construct was found to be antigenic, non-allergenic and non-toxic.Furthermore, the physicochemical properties of the vaccine suggested that it was thermally stable, with a GRAVY score of −0.592, indicating its hydrophilic nature.Based on these findings, the multi-epitope mRNA vaccine construct developed in this study has the potential to be an effective candidate against P. aeruginosa.

Population coverage prediction
The IEDB Population Coverage tool was used to measure the global population coverage of the 29 epitopes for their corresponding 38 alleles.The results indicated that the vaccine construct has the potential to cover ∼90.13% of the world's population, suggesting that it could provide broad protection against P. aeruginosa infections.

In silico immune response simulation against the vaccine
In the study, three vaccine injections were administered to simulate the immune response (Figure 3).The second and third injections elicited higher immune responses compared to the primary injection.Immunoglobulin M (IgM) levels were higher than IgG levels, and the levels of immunoglobulins remained elevated following antigen reduction, suggesting the potential emergence of immune memory and practiced immunity.Isotype switching and memory formation of the B-cell population were also observed, with the presence of B-cell isotypes persisting for a prolonged duration.In addition, an increase in CTL and HTL cells with memory generation was observed.Furthermore, macrophage

Codon optimization of the mRNA construct
To enhance the translation of the mRNA vaccine construct within host cells, codon optimization tools were utilized.The GenSmart Codon Optimization tool (G.S.) was used to optimize the vaccine sequence for efficient expression in human cells.The length of the CDS was 1824 nucleotides, and the rare codon analysis tool from G.S. was employed to evaluate the quality of the optimized construct.The CAI value was estimated to be 0.96 (Figure 4A), which is acceptable since it exceeds the cut-off value of 0.8.In addition, the optimized construct's G.C. content was evaluated, and it was found that the optimal percentage of G.C. content should be ∼30-70% to ensure efficient expression in the human host.The average G.C. percentage of the optimized construct was 76.53%.This indicates that no codons could impede translation efficiency or function, as any codons with a value lower than 30 could reduce or stop translational machinery.Overall, these analyses suggest that the codon-optimized mRNA vaccine construct can be efficiently expressed in human cells.

Prediction of the secondary structure of the mRNA vaccine
The RNAfold server was used to predict the structure of the mRNA vaccine construct.The optimized codons of the construct were used as input, and the free energies of the structure were assessed using the server.The results indicated that the mRNA vaccine construct would be stable when manufactured with the MFE of the structure, which was calculated to be −739.10kcal/mol (Figure 4B).In addition, the secondary centroid structure had a free energy of −680.30kcal/mol (Figure 4C).These findings suggest that the mRNA vaccine construct can be efficiently manufactured and is structurally stable, potentially enhancing its efficacy as a vaccine.

Prediction and validation of the secondary and tertiary structures of the translated construct
The PSIPRED web service was used by researchers to further analyze the structure of the mRNA vaccine construct and predict its secondary structure.The alpha helices that predominated in the structure are shown in Figure 5A (Supplementary file 1).
In addition, the Robetta server was used to predict the tertiary structure of the peptide (Figure 5B), and the PROCHECK server was employed to verify the stereochemical accuracy of the structure.The Ramachandran plot presented in Figure 5C indicated that ∼83.1% of the residues were in the most favored regions, 13.2% in the additionally allowed zone and 1.8% in the generously allowed regions.The overall quality factor was 93.5275.Moreover, a negative Z-score (−7.09) was predicted by the ProSA-web, indicating that the 3D protein model is highly consistent (Figure 5D).Overall, these analyses suggest that the structure of the mRNA vaccine construct is stable, accurate and consistent, potentially enhancing its efficacy as a vaccine.

Conformational B-cell epitope prediction
The ElliPro server was used by researchers to predict the conformational B-cell epitopes generated from the folding of the model protein.The results revealed the prediction of six discontinuous B-cell epitopes, with a prediction score ranging from 0.515 to 0.791 for 215 residues.The 2D and 3D models of these conformational B-cell epitopes are shown in Figure 6I and II, respectively.These findings suggest that strong B-cell immune responses against P. aeruginosa infections can potentially be elicited by the mRNA vaccine construct.

Molecular dynamics simulation
To further analyze the vaccine-TLR3 and vaccine-TLR4 complexes, molecular dynamics simulation was performed using the iMODS server, while receptor-ligand interactions were assessed.The deformable loci of the construct were represented by peaks in the deformability graph (Figures 7B and 8B), which showed amino acids with coiled shapes.Normal mode analysis (NMA) was also conducted to study and characterize protein f lexibility, with the B-factor graph (Figures 7C and 8C) depicting the relationship between NMA and PDB areas in the uploaded complex.Eigenvalues of the docked complexes are displayed in Figures 7D and 8D.Overall, these analyses indicated that the vaccine-receptor complex had a low deformation index, muscular stiffness and high stability.
In Figures 7E and 8E, the covariance matrix showed the connection between amino acid duplets scattered in dynamical regions, with red indicating correlated residues, white representing anti-correlated amino acid duplets and blue representing non-correlated residues.In addition, a connecting matrix representing the elastic network model was employed to classify which atom pairs were connected by springs (Figures 7F and 8F).Each chain of the complex was found to have high stiffness, with darker gray colors indicating stiffer regions.These findings suggest that the vaccine-receptor complex is stable, rigid and has strong intermolecular interactions, potentially enhancing its efficacy as a vaccine against P. aeruginosa.

DISCUSSION
Pseudomonas aeruginosa is a challenging pathogen due to its antibiotic resistance, and developing effective vaccines against it has become crucial [26].Research on P. aeruginosa vaccines has been ongoing for over half a century, but despite extensive efforts, there are still no approved vaccines to date [27].The complexity of P. aeruginosa's pathogenesis, diverse virulence factors, high plasticity within the lung and high diversity of serotypes are significant obstacles in developing an effective vaccine [28].Both innate and adaptive immune responses play critical roles in combating P. aeruginosa infection.As P. aeruginosa is an extracellular pathogen, humoral, mucosal or systemic opsonizing immunity is most effective in preventing bacterial colonization and infection.However, T-cell responses can also mediate protective immunity in individuals with P. aeruginosa infections [29].Despite the challenges posed by the emergence of MDR and XDR strains, complex pathogenesis, high serotype diversity, and more, continued research and collaboration among scientists may lead to the development of an effective vaccine to combat this critical health challenge [30].
Immunoinformatic approaches were used in a study to develop a novel mRNA vaccine that is safe, engineered and efficient.This mRNA-based vaccine has been shown to be effective against various viral infections such as Zika, inf luenza, rabies, coronavirus and many others [31].Recently, multiple human clinical trials have begun, indicating that mRNA vaccines are now considered to be a safe and effective alternative to subunit protein, chimeric virus and even DNA-based therapies in the form of vaccination [32].One of the benefits of mRNA-based vaccines is their ability to induce the transient expression and accumulation of selected antigens in the cytoplasm, which then triggers an immune response against the target pathogen [33].This approach may offer several advantages over traditional vaccine strategies, including ease of production, rapid development and improved efficacy.
The development of a safe and efficient mRNA vaccine using immunoinformatic approaches represents a promising advancement in the field of vaccination.With increasing preclinical evidence and ongoing clinical trials, mRNA vaccines may become a preferred option for preventing viral infections and related diseases.In this study, a novel in silico multi-epitope mRNA vaccine has been proposed to combat the infection crises caused by P. aeruginosa.The vaccine is based on the major surface proteins of P. aeruginosa that contribute to cell binding and attachment of the bacterium.This approach may offer a potential solution to the challenges posed by P. aeruginosa infections, and further research is needed to evaluate the safety and efficacy of this vaccine.To identify potential epitopes that could induce humoral or cellular responses, the target proteins were examined using webbased tools such as the IEDB database, which predicts epitopes of HTL and CTL based on immune epitope determination, and ABC pred, an online server that anticipates B-cell epitopes using an artificial machine-learning method.The evaluation of epitopes was performed using web servers to determine antigenicity, allergenicity and toxicity.Specific linkers were used to combine the epitopes.
To further refine the vaccine design, an immune simulation was conducted to validate the humoral and cellular responses of the vaccine.The vaccine construct's targeted epitopes had 38 corresponding MHC alleles.The four chosen epitopes were subjected to molecular docking analysis, as ligand-epitope interaction is essential in vaccine design.Docking analysis was performed among the chosen epitopes and their corresponding MHC alleles using ClusPro, which predicts binding affinity and bond formation between the receptor and ligands.The interactions among the epitopes and MHC pockets were also analyzed.These steps were taken to ensure that the vaccine design was optimized for maximum efficacy.
This study proposes a novel in silico multi-epitope mRNA vaccine against P. aeruginosa based on major surface proteins of the bacterium.Various bioinformatics tools were utilized to predict and evaluate epitopes, and immune simulations were conducted to validate the vaccine's effectiveness.The results of molecular docking analysis suggest strong binding affinity between the chosen epitopes and their corresponding MHC alleles, indicating the potential efficacy of the proposed vaccine.It is important to note that vaccination is only effective in individuals with a particular MHC allele that can bind the epitope.Therefore, the IEDB   population coverage tool was used to predict that the proposed vaccine would cover 90.13% of the world's population.This indicates that the vaccine has the potential to be widely effective.Moreover, to evaluate the vaccine's capacity to interact with immune receptors, the TLR-3 and TLR-4 immune receptors were docked with the vaccine construct.The findings showed that the vaccine has a strong affinity for binding to TLR-4 and TLR-3, indicating the potential for triggering both innate and adaptive immunity.This is a promising result as it suggests that the vaccine has the potential to stimulate a robust immune response.Overall, the proposed vaccine shows great potential for providing protection against P. aeruginosa infection.
The stability of the vaccine complex was investigated using molecular dynamics simulation, which showed that the proposed mRNA vaccine's peptide sequence is stable and thermostable.Immunoinformatic approaches were also used to evaluate the vaccine's antigenicity, allergenicity and hydrophilicity, and the results indicate that the vaccine is antigenic, non-allergenic and hydrophilic.In this study, the proposed in silico multi-epitope mRNA vaccine against P. aeruginosa has been evaluated for its potential effectiveness in triggering an immune response.The predicted population coverage is high, and the vaccine construct has a strong affinity for binding to immune receptors TLR-4 and TLR-3.In addition, molecular dynamics simulations indicate that the vaccine complex is stable, antigenic and non-allergenic.These findings suggest that the proposed vaccine may be a promising approach to combat P. aeruginosa infections.Overall, the study provides valuable insights into the development of effective vaccines against P. aeruginosa and highlights the potential of in silico approaches for vaccine design.

CONCLUSION
In conclusion, the proposed design of a novel multi-epitope mRNA vaccine for P. aeruginosa in this study provides a promising framework for future research in the field of vaccination against this bacterium.However, it is important to note that further in vitro and in vivo studies are necessary to confirm the findings of this study and to evaluate the vaccine's safety, efficacy and potential limitations in real-world scenarios.Successful development of an effective vaccine against P. aeruginosa could have significant implications for public health by reducing the morbidity and mortality associated with this pathogen.The proposed vaccine's high predicted population coverage and strong affinity for immune receptors TLR-4 and TLR-3 suggest that it may be a promising approach to combat P. aeruginosa infections.Overall, this study highlights the potential of in silico approaches for vaccine design and provides valuable insights into the development of effective vaccines against P. aeruginosa.

Key Points
• In designing an effective mRNA vaccine for P. aeruginosa, surface proteins critical for binding and entering the bacteria into host cells could serve as suitable targets.• The results indicated that the designed mRNA construct could be an effective and promising vaccine that requires laboratory and clinical trials.• The proposed design of a novel multi-epitope mRNA vaccine for P. aeruginosa in this study provides a promising framework for future research in the field of vaccination against this bacterium.

Figure 1 .
Figure 1.Docking between the epitopes and their corresponding MHC allele.

Figure 2 .
Figure 2. Epitopes and their corresponding MHC allele interaction using the LIGPLOT webserver.

Figure 3 .
Figure 3.In silico immune simulation against the mRNA vaccine retrieved from the C-ImmSim server (https://kraken.iac.rm.cnr.it/C-IMMSIM/).(A) The immunoglobulin production after antigen injection.(B) The B-cell population after three injections.(C) The B-cell population per state.(D) The helper Tcell population.(E) The helper T-cell population per state.(F) The cytotoxic T-cell population per state.(G) Macrophage population per state.(H) Dendritic cell population per state.(I) Cytokine and interleukin production with Simpson Index of the immune response.

Figure 4 .
Figure 4. Codon optimization and mRNA vaccine structure prediction: (A) CAI value; (B) optimal secondary structure; (C) centroid secondary structure of the vaccine mRNA retrieved using RNAfold webserver.

Figure 5 .
Figure 5. Structure prediction and validation of the peptide vaccine construct: (A) tertiary structure of the peptide using the Robetta server; (B) Ramachandran plot analysis using the PROCHECK server; (C) Z-score analysis using ProSA webserver.

Figure 6 .
Figure 6.The six predicted conformational B-cell epitopes using the ElliPro tool of the IEDB database: (I) 2D diagra m of the positions of conformational B-cell epitopes.(II) The 3D models of B-cell epitopes.The spheres represent the conformational B-cell epitopes.(A) 14 residues with a score of 0.613.(B) 37 residues with a score of 0.779.(C) 32 residues with a score of 0.791.(D) 120 residues with a score of 0.681.(E) 7 residues with a score of 0.582.(F) 5 residues with a score of 0.515.

Table 1 :
Cell type and sequence of epitope in this study

Table 2 :
Selected T-lymphocyte epitopes and their corresponding MHC alleles' protein name

Table 3 :
Docking analysis of some CTL epitopes with their corresponding MHC alleles

Table 4 :
The physicochemical properties of the translated form of the proposed mRNA vaccine activity was enhanced, while dendritic cell activity remained stable.Levels of IFN-γ and IL-2 cytokines were also increased.Epithelial cells, which are components of innate immunity, were augmented as well.Lastly, the Simpson index (D) was low, indicating a diverse immune response.Overall, these results suggest that the multi-epitope mRNA vaccine construct elicits a robust and diverse immune response against P. aeruginosa.